LLMs Cannot Find Reasoning Errors, but They Can Correct Them!
#llms #llmmistakefinding #llmoutputcorrection #bigbenchmistake #chainofthought #nlp #selfconsistency #zeroshotprompting
https://hackernoon.com/llms-cannot-find-reasoning-errors-but-they-can-correct-them
#llms #llmmistakefinding #llmoutputcorrection #bigbenchmistake #chainofthought #nlp #selfconsistency #zeroshotprompting
https://hackernoon.com/llms-cannot-find-reasoning-errors-but-they-can-correct-them
Hackernoon
LLMs Cannot Find Reasoning Errors, but They Can Correct Them! | HackerNoon
In this paper, we break down the self-correction process into two core components: mistake finding and output correction.
What Are the Benchmark Results of GPT-4-Turbo, GPT4, and GPT-3.5-Turbo?
#llms #gptbenchmarkresults #bigbenchmistake #directtracelevelprompting #cotsteplevelprompting #directsteplevelprompting #llmoutputcorrection #usingllmstofindmistakes
https://hackernoon.com/what-are-the-benchmark-results-of-gpt-4-turbo-gpt4-and-gpt-35-turbo
#llms #gptbenchmarkresults #bigbenchmistake #directtracelevelprompting #cotsteplevelprompting #directsteplevelprompting #llmoutputcorrection #usingllmstofindmistakes
https://hackernoon.com/what-are-the-benchmark-results-of-gpt-4-turbo-gpt4-and-gpt-35-turbo
Hackernoon
What Are the Benchmark Results of GPT-4-Turbo, GPT4, and GPT-3.5-Turbo? | HackerNoon
All models are given the same 3-shot prompts. We use three different prompting methods. Direct trace-level prompting involves using the whole trace as input